Multilevel FLPS

Multilevel FLPS (being tested)

FLPS based on multilevel factor model

Without random effects for latent factors 

res <- runFLPS(
  inp_data = continuous,
  # complied_stan = importModel('sem', T, F),
  outcome  = "Y",
  trt      = "trt",
  covariate =
    list(c("sex","race","pretest","stdscore"),
         c("cm_sex","cm_race")),
  lv_type = "sem",
  multilevel = T,
  lv_randomeffect = F,
  lv_model = "F =~ q1 + q2 + q3 + q4 + q5 + q6 + q7 + q8 + q9 + q10",
  group_id = "schid",
  stan_options = list(iter = 10, cores = 1, chains = 1)
)

With random effects for latent factors 


res <- runFLPS(
  inp_data = continuous,
  # complied_stan = importModel('sem', T, T),
  outcome  = "Y",
  trt      = "trt",
  covariate =
    list(c("sex","race","pretest","stdscore"),
         c("cm_sex","cm_race")),
  lv_type = "sem",
  multilevel = T,
  lv_randomeffect = T,
  lv_model = "F =~ q1 + q2 + q3 + q4 + q5 + q6 + q7 + q8 + q9 + q10",
  group_id = "schid",
  stan_options = list(iter = 10, cores = 1, chains = 1)
)

FLPS based on multilevel Latent Class analysis

Without random effects for latent classes 

binary <- binary %>%
  group_by(schid) %>%
  mutate(cm_sex = mean(sex),
         cm_race = mean(race))

res <- runFLPS(
  inp_data = binary,
  # complied_stan = importModel('irt'),
  outcome  = "Y",
  trt      = "trt",
  covariate =
    list(c("sex","race","pretest","stdscore"), # Level 1 covariates
         c("cm_sex","cm_race")),               # Level 2 covariates
  lv_type = "lca",
  multilevel = T,
  lv_randomeffect = F,
  lv_model = "F =~ q1 + q2 + q3 + q4 + q5 + q6 + q7 + q8 + q9 + q10",
  nclass = 2,
  group_id = "schid",
  stan_options = list(iter = 100, cores = 1, chains = 1)
)

With random effects for latent classes 

binary <- binary %>%
  group_by(schid) %>%
  mutate(cm_sex = mean(sex),
         cm_race = mean(race))

res <- runFLPS(
  inp_data = binary,
  # complied_stan = importModel('irt'),
  outcome  = "Y",
  trt      = "trt",
  covariate =
    list(c("sex","race","pretest","stdscore"), # Level 1 covariates
         c("cm_sex","cm_race")),               # Level 2 covariates
  lv_type = "lca",
  multilevel = T,
  lv_randomeffect = T, 
  lv_model = "F =~ q1 + q2 + q3 + q4 + q5 + q6 + q7 + q8 + q9 + q10",
  nclass = 2,
  group_id = "schid",
  stan_options = list(iter = 100, cores = 1, chains = 1)
)